Conference Proceeding Article
The recent years have seen an unprecedented boom of social network services, such as Twitter, which boasts over 200 million users. In such big social platforms, the influential users are ideal targets for viral marketing to potentially reach an audience of maximal size. Most proposed algorithms rely on the linkage structure of the respective underlying network to determine the information flow and hence indicate a users influence. From social interaction perspective, we built a model based on the dynamic user interactions constantly taking place on top of these linkage structures. In particular, in the Twitter setting we supposed a principle of balanced retweet reciprocity, and then formulated it to disclose the values of Twitter users. Our experiments on real Twitter data demonstrated that our proposed model presents different yet equally insightful ranking results. Besides, the conducted prediction test showed the correctness of our model.
Twitter, User ranking, Retweet behavior
Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Data Management and Analytics
Social Informatics: 5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013: Proceedings
City or Country
XIE, Wei; HOANG, Ai Phuong; ZHU, Feida; and LIM, Ee Peng.
Information vs Interaction: An Alternative User Ranking Model for Social Networks. (2013). Social Informatics: 5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013: Proceedings. 8238, 227-240. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1975
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